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Material Handling Systems
Published in Susmita Bandyopadhyay, Production and Operations Analysis, 2019
In the proposed material handling strategy, a set of move tasks are gathered. The trolleys automatically send their real-time status. A server that interacts with the trolleys, optimally assigns move tasks to the optimized trolleys and operators. Each trolley sends its real-time status after finishing its task so that a new task can be assigned to it. The proposed dynamic strategy contained three basic models—(i) intelligent trolleys, (ii) information exchange in real-time, and (iii) optimization of material handling tasks. Intelligent trolleys, with the help of the tags, information technology and wireless communication, interact with the other trolleys, distribution system and can have active perception about the environment. The information exchange module makes the exchange of real-time data between the intelligent trolleys and the pool of move tasks. The optimization module assigns the appropriate trolleys with the next move task optimally.
Decision-Making in Sport
Published in Paul M. Salmon, Scott McLean, Clare Dallat, Neil Mansfield, Colin Solomon, Adam Hulme, Human Factors and Ergonomics in Sport, 2020
The RPD model has been used to explain decision-making in sports for the past ten years. Decision-making refers to a rapid recognition process using experience in similar situations. Pattern-matching enables adaptation to the context in accordance with the time pressure and uncertainty of events. It is based on active perception guided by expectancies and goals. The data support the view that pattern-matching, and more specifically ‘simple match’, plays a key role in decision-making in sports, leading ACRS to adapt efficiently. Results also showed that experts use mental simulation to anticipate possible situation development where relevant cues are not available early, consider a course of action and assess its workability.
Face Recognition
Published in Yu-Jin Zhang, A Selection of Image Analysis Techniques, 2023
Non-interactive face liveness detection can distinguish live faces and prosthetic faces without the user's active perception, and without interacting with the user. Non-interactive face liveness relies on detection and analysis of the difference between the real live face images and the prosthetic image captured by cameras to distinguish live faces and prosthetic faces. Following (Xie et al. 2022), the main existing anti-spoofing method categories, and their principles and characteristics, are summarized in Table 7.7.
World models and predictive coding for cognitive and developmental robotics: frontiers and challenges
Published in Advanced Robotics, 2023
Tadahiro Taniguchi, Shingo Murata, Masahiro Suzuki, Dimitri Ognibene, Pablo Lanillos, Emre Ugur, Lorenzo Jamone, Tomoaki Nakamura, Alejandra Ciria, Bruno Lara, Giovanni Pezzulo
While active inference introduces an important perspective towards an understanding of adaptive and autonomous behaviors, an obvious behavioral imperative, the exploration-exploitation dilemma, seems in conflict with this idea because exploration, i.e. observing an uncertain aspect of the environment, would result in obtaining an unpredictable outcome [59, 60]. Indeed exploration and active perception have a central role in robot control and learning. Several tasks focus on robots' ability to explore an unknown environment [61–63]. Furthermore, in social contexts, unobservable factors such as others' intentions must be actively considered to allow for efficient human-robot collaboration [64–67].
Culture coding - a method for diversifying artefact associations in design ideation
Published in International Journal of Design Creativity and Innovation, 2022
Jana Pejoska, Eva Durall, Merja Bauters, Teemu Leinonen
According to Baron (Baron, 2007), people disregard possibilities, occurrences and evidence and make inferences that protect their favored ideas. Therefore, to open up a less biased perspective, one must be actively perceptive and aware of one’s subjective social reality among the other perceptive realities (Dourish, 2004). One approach, that has been proposed, to overcome these challenges is to expose others’ ideas to users or create more perspectives about the design context and its elements (Chan et al., 2017; Mackeprang et al., 2018). Merleau-Ponty’s ‘space of situation (Merleau-Ponty, 1996) highlights that the environment for which a design is developed should be regarded as the designers’ extension of their own physical body, which would serve to provide the designer with different perceptual abilities. Having an active perception means considering perception not only as embedded in the surrounding world but also as an enactment of the surrounding world. Perception is mainly based on sensory-guided action(s) and the cognitive structures are the result of the sensorimotor patterns that enable the senses to guide the action (Varela et al., 2017). This could particularly challenge the designer’s way of making associations, which is crucial as a form of making diverse assumptions in the design ideation process. This is discussed, for instance, by Diethlem as the processes of embodied design thinking, where the design implications are considered by the mind in the form of brain-body-in-the-world (Diethelm, 2019). The approach to design processes as embodied are actions toward uncovering the cognitive biases of the designer, leading to having novel understanding. In this way by using embodied perspectives, we support newly formed practices in design for technology with benefits that can be especially valuable in design that seeks to reform the human-technology relations.
Semiotically adaptive cognition: toward the realization of remotely-operated service robots for the new normal symbiotic society
Published in Advanced Robotics, 2021
Tadahiro Taniguchi, Lotfi El Hafi, Yoshinobu Hagiwara, Akira Taniguchi, Nobutaka Shimada, Takanobu Nishiura
In particular, active exploration by robots in simultaneous localization and mapping (active SLAM) has long been studied [42–44]. In active SLAM, when the robot simultaneously generates a map and estimates its self-position in the environment, it actively selects the next destination. For objects, active perception and exploration have been proposed for active selection of the information to be observed next when the robot identifies or learns the category of the object [45, 46].